Intelligent monitoring system of coal yard environment based on 5G technology

Abstract

The present invention discloses an intelligent monitoring system for coal yard environment based on 5G technology, and relates to the field of intelligent monitoring technology. In order to solve the problems in the prior art that, although manpower is greatly saved, there are still limited monitoring ranges of drones, blind spots in monitoring are prone to occur, and the cost is high, the data transmission speed is slow, and the processing and analysis capabilities are insufficient; the intelligent monitoring system for coal yard environment based on 5G technology includes a front-end detection unit, a central control unit, and an intelligent monitoring terminal; based on the 5G network, various environmental data in the coal yard are transmitted in real time, providing managers with real-time feedback on the environmental conditions of the coal yard, which helps to timely discover and deal with potential safety hazards, and reasonably configure and dispatch according to the real-time conditions of the coal yard environment to ensure that the coal yard environment is always kept within a safe and healthy range. Through data visualization technology, the coal yard environmental data is displayed to managers in the form of charts, animations, etc., so that they can intuitively understand the environmental conditions of the coal yard.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to a coal yard environment intelligent monitoring system based on 5G technology. Background Art

[0002] Traditional coal yard environmental monitoring may mainly rely on manual inspections and fixed monitoring equipment, which usually have problems such as low communication rate, limited monitoring range, and insufficient image analysis and processing. Regarding the intelligent monitoring system of coal yard environment, the Chinese patent with publication number: CN114003068B discloses a power plant coal yard temperature monitoring system and method based on drones, including a ground station system, a drone system, an environmental data acquisition system, and a data processing system; the drone system includes a drone, a positioning system, an infrared thermometer, and a camera; the ground station system obtains the preset flight route of the drone; the drone control system controls the drone to fly according to the preset flight route of the drone; the positioning system obtains the real-time location information of the drone; the infrared thermometer collects the surface temperature information of the power plant coal yard; the camera collects the image information of the power plant coal yard; the environmental data acquisition system collects the environmental data of the power plant coal yard; the data processing system obtains the coal pile temperature distribution data of the coal yard of the power plant according to the image information of the power plant coal yard, the surface temperature information of the power plant coal yard, and the environmental data of the power plant coal yard. Compared with the existing method, it greatly saves manpower and realizes real-time monitoring of the coal yard temperature.

[0003] Although the existing technology greatly saves manpower, there are still problems such as limited monitoring range of drones, prone to blind spots, high costs, slow data transmission speeds, and insufficient processing and analysis capabilities. It is impossible to promptly and effectively discover and deal with safety hazards such as spontaneous combustion in coal yards. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent monitoring system for the coal yard environment based on 5G technology, which can be reasonably configured and scheduled according to the real-time conditions of the coal yard environment, ensure that the coal yard environment always remains within a safe and healthy range, and improve the overall quality of the coal yard environment, so as to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The coal yard environment intelligent monitoring system based on 5G technology includes:

[0007] Front-end detection unit for:

[0008] Deploy at least one infrared dual-view online monitoring device in the coal yard monitoring environment to obtain environmental monitoring data in real time, and transmit the obtained environmental monitoring data to the central control unit based on the 5G network. At the same time, receive and execute the control instructions issued by the central control unit to control the intelligent monitoring terminal to respond;

[0009] The infrared dual-view online monitoring device includes an infrared thermal imager and a visible light camera, wherein the infrared thermal imager is used to obtain an infrared thermal image of the coal pile, and the visible light camera is used to obtain a visible light video image;

[0010] A central control unit is used to read the environmental monitoring data, process and analyze the received infrared thermal images, obtain the spontaneous combustion potential points, and issue control instructions to control the terminals where the natural potential points are located to issue early warning alarms;

[0011] Intelligent monitoring terminals, including query terminals, control stations and analysis terminals, are used to access the environmental monitoring data obtained by the monitoring front-end unit in real time through the network, and generate various reports for visual display according to user needs.

[0012] Furthermore, the front-end detection unit includes:

[0013] The infrared imaging module is used to continuously scan the coal yard based on an infrared thermal imager, capture infrared thermal radiation and generate infrared thermal images, and pre-process the collected infrared thermal images;

[0014] The temperature measurement module is used to extract temperature data from the pre-processed infrared thermal image, calibrate the extracted temperature data, eliminate the influence of environmental factors on the temperature measurement results, and obtain calibrated temperature data;

[0015] The communication control module is used to package the pre-processed infrared thermal image and the calibrated temperature data based on the timestamp to generate environmental monitoring data, encode the IP data based on the infrared thermal imager, and use the 5G network to transmit the encoded environmental monitoring data to the central control unit in real time;

[0016] The communication control module is also used to monitor the control instructions sent by the central control unit in real time. After receiving the control instructions, it parses them and performs corresponding operations according to the content of the instructions.

[0017] Furthermore, the communication control module further includes:

[0018] Configure and test the network connection required by the intelligent monitoring terminal, assign a unique network address to each infrared dual-view online monitoring device, and set the initial parameters for system operation;

[0019] Calibrate each infrared thermal imager based on the unique network address, determine and number the monitoring points of each infrared dual-view online monitoring device, and set the focal length of each infrared thermal imager according to the distance of each monitoring point and shooting requirements;

[0020] Each infrared thermal imager is equipped with a pan-tilt platform, and a cruising path of the pan-tilt platform is planned according to the determined monitoring points. According to the planned cruising path, the pan-tilt platform is controlled to move and shoot according to the preset monitoring points.

[0021] Furthermore, the central control unit comprises:

[0022] A data reading module is used to read the environmental monitoring data, determine the data type of the environmental monitoring data, and classify the data based on the data type of the environmental monitoring data to obtain infrared thermal image data, temperature data, video stream data and device status data;

[0023] The data processing module is used to compare and analyze infrared thermal images and temperature data, and to make auxiliary judgments in combination with video stream data to identify the location and range of potential spontaneous combustion hazards and determine the severity of potential spontaneous combustion hazards;

[0024] The terminal control module is used to formulate corresponding early warning strategies according to the severity and location of the identified spontaneous combustion hazard points, generate corresponding control instructions, and send the generated control instructions to the front-end detection unit through the 5G network.

[0025] Furthermore, the data processing module includes:

[0026] The infrared image processing submodule is used to extract target key features from the temperature data features in the infrared thermal image data. The target key features include temperature distribution and hot spot areas. The temperature change trend of the coal pile is analyzed according to the extracted target key features to determine whether there is an abnormal temperature area.

[0027] The video monitoring processing submodule is used to process the video stream data and perform image recognition on the processed video stream data to determine whether there is any abnormality;

[0028] The fire prevention warning submodule is used to make comprehensive judgments and warnings based on the judgment results of the infrared image processing submodule and the video monitoring processing submodule, trigger the warning mechanism, and at the same time, send alarm information to relevant personnel.

[0029] Furthermore, the infrared image processing submodule is specifically:

[0030] Decode the pixel values ​​of the external thermal image data, convert the pixel values ​​into corresponding temperature values, and construct a temperature data matrix, in which each pixel position corresponds to a temperature value;

[0031] Based on the acquired temperature data, the average temperature of the entire coal pile area is calculated, the statistical characteristics of the temperature data are analyzed, and the discrete degree and shape of the temperature distribution are determined;

[0032] A temperature threshold is set according to the normal temperature range of the coal pile and the spontaneous combustion warning standard, and pixel points exceeding the temperature threshold at the temperature data matrix mark are traversed to form potential hot spots;

[0033] Perform time series analysis on continuous multi-frame infrared thermal images to determine the changing characteristics of temperature data, and perform temperature prediction based on the time series prediction model to determine potential abnormal temperature areas;

[0034] Based on the potential hot spot area and the potential abnormal temperature area, it is comprehensively judged whether there is an abnormal temperature area, and the position and range of the abnormal temperature area in the external thermal image data are determined.

[0035] Furthermore, the video surveillance processing submodule is specifically:

[0036] After extracting the video stream data, the video stream data is framed to obtain a target image, obtain pixel values ​​corresponding to the target image, and determine the monitoring area of ​​the target image according to the pixel values ​​corresponding to the target image;

[0037] The position of the abnormal temperature area detected in the infrared image processing submodule in the processed video stream data is determined based on the area of ​​the monitoring area, and image recognition is performed on the position in the video stream data to determine whether there is an abnormality in the video stream data.

[0038] Furthermore, the intelligent monitoring terminal includes:

[0039] The query and statistics module is used to perform real-time query on all environmental monitoring data and statistics and analysis on historical data, and provides the association, query, statistics and analysis functions of environmental monitoring data;

[0040] The report generation module is used to generate reports containing detailed information and statistical results based on the data provided by the query statistics module, and to generate various reports according to user needs for visual display;

[0041] The backend management module is used to access the environmental monitoring data obtained by the monitoring front-end unit in real time, and to monitor the network connection status and equipment operation status of each terminal in real time.

[0042] Further, planning a cruising path of the PTZ according to the determined monitoring points includes:

[0043] Divide the coal yard area into multiple monitoring areas, determine the location coordinates of each monitoring point, and determine the distribution of monitoring points in each monitoring area based on the location coordinates;

[0044] The cruise gain of each monitoring area is determined according to the distribution of monitoring points in each monitoring area, the building structure of the area, and the straight-line distance between each monitoring point in each monitoring area;

[0045] Determine the type of cruise path of the PTZ in each monitoring area based on the cruise gain of each monitoring area, wherein the cruise path types include: straight cruise and curved cruise;

[0046] The straight-line distance of the first monitoring point in the first monitoring area whose cruise path type is straight-line cruise is set as the straight-line cruise path of the PTZ;

[0047] Setting a plurality of curved cruising paths according to the relative position relationship between the second monitoring points in the second monitoring area whose cruising path type is curved cruising;

[0048] Obtain the path points of each curved cruising path, calculate the gimbal's cruising attitude according to the path points, and select the first curved cruising path that meets the attitude requirements according to the gimbal's cruising attitude;

[0049] Acquire multiple key monitoring areas in the coal yard area, and acquire visual features of each key monitoring area on each first curved cruising path of the PTZ;

[0050] According to determining the visual conflict path points in each first curved cruising path and determining the proportion of the visual conflict path points to all the path points;

[0051] Selecting a second curved cruising path whose ratio is less than or equal to a preset ratio value, and calculating an obstacle avoidance risk coefficient of each second curved cruising path;

[0052] Selecting a third curved cruising path with the smallest obstacle avoidance risk coefficient in each second monitoring area as the curved cruising path of the second monitoring area;

[0053] All straight cruise paths and curved cruise paths are integrated according to the relative position relationship of the monitoring area to obtain the overall cruise path of the PTZ.

[0054] Furthermore, the obstacle avoidance risk coefficient of each second curve cruising path is calculated, including:

[0055] Obtain the number of obstacles and the area of ​​each obstacle on each second curve cruising path;

[0056] Determine the difficulty index of the gimbal avoiding danger at the path boundary without deviating from each second curve cruising path according to the area of ​​each obstacle;

[0057] The obstacle avoidance risk coefficient of each second curve cruising path is calculated based on the difficulty index of the gimbal avoiding the obstacle at the path boundary of each second curve cruising path:

[0058]

[0059] Among them, S i Expressed as the obstacle avoidance risk coefficient of the i-th second curve cruising path, β i is represented by the curvature coefficient of the i-th second curve cruising path, Mi is represented by the number of obstacles in the i-th second curve cruising path, j is represented by the j-th obstacle, and D j It is expressed as the risk avoidance difficulty coefficient of the gimbal not deviating from the path boundary of the i-th second curve cruising path when passing the j-th obstacle, μ j It is expressed as the attitude stabilization gain factor required by the gimbal when avoiding the j-th obstacle.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] Based on the real-time transmission of various environmental data in the coal yard over the 5G network, managers are provided with real-time feedback on the environmental conditions of the coal yard, which helps to promptly discover and deal with potential safety hazards, and make reasonable configurations and dispatches based on the real-time conditions of the coal yard environment to ensure that the coal yard environment always remains within a safe and healthy range, thereby improving the overall quality of the coal yard environment. Through data visualization technology, the coal yard environmental data is displayed to managers in the form of charts, animations, etc., so that they can intuitively understand the environmental conditions of the coal yard. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a module diagram of the coal yard environment intelligent monitoring system based on 5G technology of the present invention;

[0063] Figure 2 This is an architecture diagram of the coal yard environment intelligent monitoring system based on 5G technology of the present invention;

[0064] Figure 3 This is a monitoring flow chart of the infrared thermal imager of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] In order to solve the technical problems in the existing technology, although it greatly saves manpower, there are still problems such as limited monitoring range of drones, easy to have monitoring blind spots, high cost, slow data transmission speed, insufficient processing and analysis capabilities, and inability to timely and effectively discover and deal with safety hazards such as spontaneous combustion in coal yards, please refer to Figure 1-3 , this embodiment provides the following technical solutions:

[0067] The coal yard environment intelligent monitoring system based on 5G technology includes:

[0068] Front-end detection unit for:

[0069] Deploy at least one infrared dual-view online monitoring device in the coal yard monitoring environment to obtain environmental monitoring data in real time, and transmit the obtained environmental monitoring data to the central control unit based on the 5G network. At the same time, receive and execute the control instructions issued by the central control unit to control the intelligent monitoring terminal to respond;

[0070] The infrared dual-view online monitoring device includes an infrared thermal imager and a visible light camera, wherein the infrared thermal imager is used to obtain an infrared thermal image of the coal pile, and the visible light camera is used to obtain a visible light video image;

[0071] In this embodiment, the infrared dual-view online monitoring device performs all-round monitoring of the entire coal pile. Three pan-tilt type infrared dual-view online monitoring devices, a total of six devices, are installed at appropriate positions under the horseway of each circular coal shed. The installation positions of the three devices form an angle of 120° with each other.

[0072] A central control unit is used to read the environmental monitoring data, process and analyze the received infrared thermal images, obtain the spontaneous combustion potential points, and issue control instructions to control the terminals where the natural potential points are located to issue early warning alarms;

[0073] Intelligent monitoring terminals, including query terminals, control stations and analysis terminals, are used to access the environmental monitoring data obtained by the monitoring front-end unit in real time through the network, and generate various reports for visual display according to user needs, such as temperature change trend charts, spontaneous combustion hazard point distribution charts, etc., to help users deeply analyze the safety status of the coal yard and propose targeted improvement measures. At the same time, according to the control instructions obtained, corresponding operations are executed, and the execution results and equipment status information are fed back to the central control unit through the network;

[0074] In this embodiment, the intelligent monitoring terminal includes:

[0075] The query and statistics module is used to query all environmental monitoring data in real time and to perform statistics and analysis on historical data. It provides the association, query, statistics and analysis functions of environmental monitoring data and supports multiple query methods, such as query by time range and query by data type, to meet different query needs of users, help users analyze data trends and rules, and provide support for decision-making;

[0076] The report generation module is used to generate reports containing detailed information and statistical results based on the data provided by the query statistics module, and to generate various reports according to user needs for visual display so that users can understand the monitoring data more intuitively;

[0077] The background management module is used to access the environmental monitoring data obtained by the monitoring front-end unit in real time, monitor the network connection status and equipment operation status of each terminal in real time, and ensure the normal operation of the system and the security of data.

[0078] In this embodiment, various environmental data in the coal yard are transmitted in real time based on the 5G network, providing managers with real-time feedback on the environmental conditions of the coal yard. The central control unit can quickly process and analyze the received infrared thermal images, promptly discover potential spontaneous combustion hazards and take corresponding early warning measures, and make reasonable configuration and scheduling according to the real-time conditions of the coal yard environment. By comparing and analyzing infrared thermal images and visible light images, potential spontaneous combustion hazards and other abnormal conditions can be identified more accurately. Through data visualization technology, the coal yard environmental data can be displayed to managers in the form of charts, animations, etc., so that they can intuitively understand the environmental conditions of the coal yard, which is helpful to improve the safety management level of the coal yard.

[0079] In this embodiment, the front-end detection unit includes:

[0080] The infrared imaging module is used to continuously scan the coal yard based on an infrared thermal imager, capture infrared thermal radiation and generate infrared thermal images, and pre-process the collected infrared thermal images;

[0081] The temperature measurement module is used to extract temperature data from the preprocessed infrared thermal image, calibrate the extracted temperature data, eliminate the influence of environmental factors such as atmospheric temperature and humidity on the temperature measurement results, and obtain calibrated temperature data;

[0082] The communication control module is used to package the pre-processed infrared thermal image and the calibrated temperature data based on the timestamp to generate environmental monitoring data, encode the IP data based on the infrared thermal imager, and use the 5G network to transmit the encoded environmental monitoring data to the central control unit in real time;

[0083] The communication control module is also used to monitor the control instructions sent by the central control unit in real time. After receiving the control instructions, it parses them and performs corresponding operations according to the contents of the instructions, such as adjusting the scanning range of the infrared thermal imager, changing the threshold of the temperature measurement module, etc.

[0084] In this embodiment, the communication control module further includes:

[0085] Configure and test the network connection required by the intelligent monitoring terminal to ensure the stability and security of the 5G network or other communication methods, front-end detection units, including infrared thermal imagers, visible light CCDs, pan / tilt servos, etc., and assign a unique network address to each infrared dual-view online monitoring device to ensure that the central control unit can accurately identify and control each device, and set the initial parameters of the system operation, such as data transmission frequency, log recording method, etc.;

[0086] Calibrate each infrared thermal imager based on the unique network address, including adjusting parameters such as temperature range and sensitivity to ensure temperature measurement accuracy, determine and number the monitoring points of each infrared dual-view online monitoring device, including position coordinates, horizontal rotation angle, vertical rotation angle and monitoring time, and set the focal length of each infrared thermal imager according to the distance of each monitoring point and shooting requirements;

[0087] A gimbal is provided for each infrared thermal imager, and a cruising path of the gimbal is planned according to the determined monitoring points. According to the planned cruising path, the gimbal is controlled to move and shoot according to the preset monitoring points. During the cruising process, the cruising path and parameters are adjusted in real time according to actual conditions, such as weather changes, equipment status, etc. The parameters of the infrared thermal imager, such as temperature measurement range, contrast, etc., are adjusted according to shooting requirements and environmental conditions to obtain the best shooting effect, and instructions such as cruise start, pause, and continue are sent to control the cruising state of the gimbal;

[0088] Among them, for the target monitoring point, a control command is sent to adjust the position and parameters of the infrared thermal imager for shooting;

[0089] In this embodiment, device status information, such as the working status and temperature data of the infrared thermal imager, is obtained based on the query instruction sent by the user.

[0090] In this embodiment, the coal yard is continuously scanned by the infrared imaging module, and infrared thermal radiation can be captured in real time and infrared thermal images can be generated. Temperature data can be extracted and calibrated, eliminating the influence of environmental factors on the temperature measurement results, thereby realizing accurate monitoring of the coal yard temperature. The stability and security of the 5G network or other communication methods are ensured by configuring and testing the network connection required by the intelligent monitoring terminal. At the same time, a unique network address is assigned to each infrared dual-view online monitoring device, and the initial parameters of the system operation are set, thereby realizing intelligent configuration and management of the equipment. Control instructions are sent to the target monitoring point to adjust the position and parameters of the infrared thermal imager for shooting, further improving the flexibility and accuracy of monitoring.

[0091] In this embodiment, the central control unit includes:

[0092] A data reading module is used to read the environmental monitoring data, determine the data type of the environmental monitoring data, and classify the data based on the data type of the environmental monitoring data to obtain infrared thermal image data, temperature data, video stream data and device status data;

[0093] The data processing module is used to compare and analyze infrared thermal images and temperature data, and to make auxiliary judgments in combination with video stream data to identify the location and range of potential spontaneous combustion hazards and determine the severity of potential spontaneous combustion hazards;

[0094] The terminal control module is used to formulate corresponding early warning strategies, including early warning levels and methods, according to the severity and location of the identified spontaneous combustion hazard points, and generate corresponding control instructions, including instructing the front-end detection unit to adjust the scanning range, increase the monitoring frequency, etc., and send the generated control instructions to the front-end detection unit through the 5G network.

[0095] In this embodiment, by comparing and analyzing infrared thermal images and temperature data and combining video stream data for auxiliary judgment, the location and range of spontaneous combustion risk points can be accurately identified, and the severity of the spontaneous combustion risk points can be determined, thereby improving the accuracy and reliability of spontaneous combustion risk detection. According to the severity and location of the identified spontaneous combustion risk points, corresponding early warning strategies can be intelligently formulated, and rapid and effective responses can be made according to specific circumstances. The spontaneous combustion risks of the coal yard can be discovered and dealt with in a timely manner, and the occurrence of fire accidents can be effectively prevented, thereby significantly improving the safe operation level of the coal yard.

[0096] In this embodiment, the data processing module includes:

[0097] The infrared image processing submodule is used to extract target key features from the temperature data features in the infrared thermal image data. The target key features include temperature distribution and hot spot areas. The temperature change trend of the coal pile is analyzed according to the extracted target key features to determine whether there is an abnormal temperature area. Specifically:

[0098] Decode the pixel values ​​of the external thermal image data, convert the pixel values ​​into corresponding temperature values, and construct a temperature data matrix, in which each pixel position corresponds to a temperature value;

[0099] Based on the acquired temperature data, the average temperature of the entire coal pile area is calculated, the statistical characteristics of the temperature data are analyzed, and the discrete degree and shape of the temperature distribution are determined;

[0100] A temperature threshold is set according to the normal temperature range of the coal pile and the spontaneous combustion warning standard, and pixel points exceeding the temperature threshold at the temperature data matrix mark are traversed to form potential hot spots;

[0101] Perform time series analysis on continuous multi-frame infrared thermal images to determine the changing characteristics of temperature data, and perform temperature prediction based on the time series prediction model to determine potential abnormal temperature areas;

[0102] Comprehensively judging whether there is an abnormal temperature area based on the potential hot spot area and the potential abnormal temperature area, and determining the position and range of the abnormal temperature area in the external thermal image data;

[0103] The basis for judging abnormal temperature areas may include: the temperature value of the hot spot area exceeds the preset threshold, the temperature change trend is abnormal, such as rapid increase, the hot spot area continues to exist in multiple consecutive frames of images, etc.;

[0104] The video monitoring processing submodule is used to process the video stream data and perform image recognition on the processed video stream data to determine whether there is an abnormality. Specifically:

[0105] After extracting the video stream data, the video stream data is framed to obtain a target image, obtain pixel values ​​corresponding to the target image, and determine the monitoring area of ​​the target image according to the pixel values ​​corresponding to the target image;

[0106] Determine the position of the abnormal temperature area detected in the infrared image processing submodule in the processed video stream data based on the area of ​​the monitored area, perform image recognition on the position in the video stream data, and determine whether there is an abnormality in the video stream data. The abnormality may be manifested as flames, smoke, illegal intrusion of personnel, etc.

[0107] The fire prevention warning submodule is used to make comprehensive judgments and warnings based on the judgment results of the infrared image processing submodule and the video monitoring processing submodule, trigger the warning mechanism, and at the same time, send alarm information to relevant personnel. When an alarm is generated, the system automatically controls the start-up of existing cooling water spraying devices to eliminate the hidden dangers of spontaneous combustion in time and realize on-site linkage.

[0108] In this embodiment, the infrared image processing submodule is used to effectively extract key features such as temperature distribution and hot spots in the infrared thermal image data, and the temperature change trend and abnormal temperature areas of the coal pile are accurately determined through time series analysis and prediction models. The video monitoring processing submodule can process video stream data in real time, and through image recognition technology, it can determine whether there are abnormal conditions such as flames, smoke, and illegal intrusion of personnel in the coal yard, which helps to timely discover and deal with potential safety hazards and reduce the cost and risk of manual inspections. The fire prevention warning submodule makes a comprehensive judgment based on the results of infrared image processing and video monitoring processing. Once the warning mechanism is triggered, it can send alarm information to relevant personnel in time and automatically control the start-up of cooling water spraying and other devices. The comprehensive warning and on-site linkage method ensures that the hidden dangers of spontaneous combustion can be dealt with in a timely and effective manner, thereby improving the safe operation level of the coal yard.

[0109] In one embodiment, planning a cruising path of the PTZ according to the determined monitoring points includes:

[0110] Divide the coal yard area into multiple monitoring areas, determine the location coordinates of each monitoring point, and determine the distribution of monitoring points in each monitoring area based on the location coordinates;

[0111] The cruise gain of each monitoring area is determined according to the distribution of monitoring points in each monitoring area, the building structure of the area, and the straight-line distance between each monitoring point in each monitoring area;

[0112] Determine the type of cruise path of the PTZ in each monitoring area based on the cruise gain of each monitoring area, wherein the cruise path types include: straight cruise and curved cruise;

[0113] The straight-line distance of the first monitoring point in the first monitoring area whose cruise path type is straight-line cruise is set as the straight-line cruise path of the PTZ;

[0114] Setting a plurality of curved cruising paths according to the relative position relationship between the second monitoring points in the second monitoring area whose cruising path type is curved cruising;

[0115] Obtain the path points of each curved cruising path, calculate the gimbal's cruising attitude according to the path points, and select the first curved cruising path that meets the attitude requirements according to the gimbal's cruising attitude;

[0116] Acquire multiple key monitoring areas in the coal yard area, and acquire visual features of each key monitoring area on each first curved cruising path of the PTZ;

[0117] According to determining the visual conflict path points in each first curved cruising path and determining the proportion of the visual conflict path points to all the path points;

[0118] Selecting a second curved cruising path whose ratio is less than or equal to a preset ratio value, and calculating an obstacle avoidance risk coefficient of each second curved cruising path;

[0119] Selecting a third curved cruising path with the smallest obstacle avoidance risk coefficient in each second monitoring area as the curved cruising path of the second monitoring area;

[0120] All straight cruise paths and curved cruise paths are integrated according to the relative position relationship of the monitoring area to obtain the overall cruise path of the PTZ.

[0121] The beneficial effects of the above technical solution are: by conducting multi-dimensional safety assessment and shooting effect assessment on the curved cruising path of each monitoring area, it is possible to maximize the stability and reliability of the gimbal cruising path while ensuring the shooting effect, laying the foundation for subsequent fire monitoring and improving practicality and stability.

[0122] In one embodiment, calculating the obstacle avoidance risk coefficient of each second curved cruising path includes:

[0123] Obtain the number of obstacles and the area of ​​each obstacle on each second curve cruising path;

[0124] Determine the difficulty index of the gimbal avoiding danger at the path boundary without deviating from each second curve cruising path according to the area of ​​each obstacle;

[0125] The obstacle avoidance risk coefficient of each second curve cruising path is calculated based on the difficulty index of the gimbal avoiding the obstacle at the path boundary of each second curve cruising path:

[0126]

[0127] Among them, S i Expressed as the obstacle avoidance risk coefficient of the i-th second curve cruising path, β i is represented by the curvature coefficient of the i-th second curve cruising path, Mi is represented by the number of obstacles in the i-th second curve cruising path, j is represented by the j-th obstacle, and D j It is expressed as the risk avoidance difficulty coefficient of the gimbal not deviating from the path boundary of the i-th second curve cruising path when passing the j-th obstacle, μ j It is expressed as the attitude stabilization gain factor required by the gimbal when avoiding the j-th obstacle.

[0128] The beneficial effect of the above technical solution is: by using the curvature of the curved cruise path and the speed and attitude gain when avoiding obstacles to determine the obstacle avoidance risk coefficient, the obstacle avoidance difficulty and risk of the gimbal on each curved cruise path can be accurately evaluated, and the safest curved cruise path can be selected, thereby improving safety and the working efficiency and stability of the gimbal.

[0129] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The intelligent monitoring system for coal yard environment based on 5G technology is characterized by: include: Front-end detection unit for: Deploy at least one infrared dual-view online monitoring device in the coal yard monitoring environment to obtain environmental monitoring data in real time, and transmit the obtained environmental monitoring data to the central control unit based on the 5G network. At the same time, receive and execute the control instructions issued by the central control unit to control the intelligent monitoring terminal to respond; The infrared dual-view online monitoring device includes an infrared thermal imager and a visible light camera, wherein the infrared thermal imager is used to obtain an infrared thermal image of the coal pile, and the visible light camera is used to obtain a visible light video image; A central control unit is used to read the environmental monitoring data, process and analyze the received infrared thermal images, obtain the potential points of spontaneous combustion, and issue control instructions to control the terminal where the potential points of spontaneous combustion are located to issue a warning alarm; Intelligent monitoring terminals, including query terminals, control stations and analysis terminals, are used to access the environmental monitoring data obtained by the monitoring front-end unit in real time through the network, and generate various reports for visual display according to user needs; The front-end detection unit carries a pan-tilt for each infrared thermal imager, plans a cruising path of the pan-tilt according to the determined monitoring points, controls the pan-tilt to move and shoot according to the preset monitoring points according to the planned cruising path, and plans the cruising path of the pan-tilt according to the determined monitoring points, including: Divide the coal yard area into multiple monitoring areas, determine the location coordinates of each monitoring point, and determine the distribution of monitoring points in each monitoring area based on the location coordinates; The cruise gain of each monitoring area is determined according to the distribution of monitoring points in each monitoring area, the building structure of the area, and the straight-line distance between each monitoring point in each monitoring area; Determine the type of cruise path of the PTZ in each monitoring area based on the cruise gain of each monitoring area, wherein the cruise path types include: straight cruise and curved cruise; The straight-line distance of the first monitoring point in the first monitoring area whose cruise path type is straight-line cruise is set as the straight-line cruise path of the PTZ; Setting a plurality of curved cruising paths according to the relative position relationship between the second monitoring points in the second monitoring area whose cruising path type is curved cruising; Obtain the path points of each curved cruising path, calculate the gimbal's cruising attitude according to the path points, and select the first curved cruising path that meets the attitude requirements according to the gimbal's cruising attitude; Acquire multiple key monitoring areas in the coal yard area, and acquire visual features of each key monitoring area on each first curved cruising path of the PTZ; According to determining the visual conflict path points in each first curved cruising path and determining the proportion of the visual conflict path points to all the path points; Selecting a second curved cruising path whose ratio is less than or equal to a preset ratio value, and calculating an obstacle avoidance risk coefficient of each second curved cruising path; Selecting a third curved cruising path with the smallest obstacle avoidance risk coefficient in each second monitoring area as the curved cruising path of the second monitoring area; Integrate all straight cruise paths and curved cruise paths according to the relative position relationship of the monitoring area to obtain the overall cruise path of the PTZ; Calculate the obstacle avoidance risk factor for each second curve cruise path, including: Obtain the number of obstacles and the area of ​​each obstacle on each second curve cruising path; Determine the difficulty index of the gimbal avoiding danger at the path boundary without deviating from each second curve cruising path according to the area of ​​each obstacle; The obstacle avoidance risk coefficient of each second curve cruising path is calculated based on the difficulty index of the gimbal avoiding the obstacle at the path boundary of each second curve cruising path: Among them, S i Expressed as the obstacle avoidance risk coefficient of the i-th second curve cruising path, β i is represented by the curvature coefficient of the i-th second curve cruising path, Mi is represented by the number of obstacles in the i-th second curve cruising path, j is represented by the j-th obstacle, and D j It is expressed as the risk avoidance difficulty coefficient of the gimbal not deviating from the path boundary of the i-th second curve cruising path when passing the j-th obstacle, μ j It is represented as the attitude stabilization gain factor required by the gimbal when avoiding the jth obstacle; The central control unit includes: a data processing module, including an infrared image processing submodule and a video monitoring processing submodule; Infrared image processing submodule, specifically: Decode the pixel values ​​of the external thermal image data, convert the pixel values ​​into corresponding temperature values, and construct a temperature data matrix, in which each pixel position corresponds to a temperature value; Based on the acquired temperature data, the average temperature of the entire coal pile area is calculated, the statistical characteristics of the temperature data are analyzed, and the discrete degree and shape of the temperature distribution are determined; A temperature threshold is set according to the normal temperature range of the coal pile and the spontaneous combustion warning standard, and pixel points exceeding the temperature threshold at the temperature data matrix mark are traversed to form potential hot spots; Perform time series analysis on continuous multi-frame infrared thermal images to determine the changing characteristics of temperature data, and perform temperature prediction based on the time series prediction model to determine potential abnormal temperature areas; Comprehensively judging whether there is an abnormal temperature area based on the potential hot spot area and the potential abnormal temperature area, and determining the position and range of the abnormal temperature area in the external thermal image data; Video surveillance processing submodule, specifically: After extracting the video stream data, the video stream data is framed to obtain a target image, obtain pixel values ​​corresponding to the target image, and determine the monitoring area of ​​the target image according to the pixel values ​​corresponding to the target image; The position of the abnormal temperature area detected in the infrared image processing submodule in the processed video stream data is determined based on the area of ​​the monitoring area, and image recognition is performed on the position in the video stream data to determine whether there is an abnormality in the video stream data.

2. The coal yard environment intelligent monitoring system based on 5G technology as claimed in claim 1 is characterized by: Front-end detection unit, including: The infrared imaging module is used to continuously scan the coal yard based on an infrared thermal imager, capture infrared thermal radiation and generate infrared thermal images, and pre-process the collected infrared thermal images; The temperature measurement module is used to extract temperature data from the pre-processed infrared thermal image, calibrate the extracted temperature data, eliminate the influence of environmental factors on the temperature measurement results, and obtain calibrated temperature data; The communication control module is used to package the pre-processed infrared thermal image and the calibrated temperature data based on the timestamp to generate environmental monitoring data, encode the IP data based on the infrared thermal imager, and use the 5G network to transmit the encoded environmental monitoring data to the central control unit in real time; The communication control module is also used to monitor the control instructions sent by the central control unit in real time. After receiving the control instructions, it parses them and performs corresponding operations according to the content of the instructions.

3. The coal yard environment intelligent monitoring system based on 5G technology as claimed in claim 2 is characterized by: The communication control module further includes: Configure and test the network connection required by the intelligent monitoring terminal, assign a unique network address to each infrared dual-view online monitoring device, and set the initial parameters for system operation; Based on the unique network address, each infrared thermal imager is calibrated, the monitoring points of each infrared dual-view online monitoring device are determined and numbered, and the focal length of each infrared thermal imager is set according to the distance of each monitoring point and the shooting requirements.

4. The coal yard environment intelligent monitoring system based on 5G technology as claimed in claim 3 is characterized by: Central control unit, including: A data reading module is used to read the environmental monitoring data, determine the data type of the environmental monitoring data, and classify the data based on the data type of the environmental monitoring data to obtain infrared thermal image data, temperature data, video stream data and device status data; The data processing module is used to compare and analyze infrared thermal images and temperature data, and to make auxiliary judgments in combination with video stream data to identify the location and range of potential spontaneous combustion hazards and determine the severity of potential spontaneous combustion hazards; The terminal control module is used to formulate corresponding early warning strategies according to the severity and location of the identified spontaneous combustion hazard points, generate corresponding control instructions, and send the generated control instructions to the front-end detection unit through the 5G network.

5. The coal yard environment intelligent monitoring system based on 5G technology as claimed in claim 4 is characterized by: Data processing module, including: The infrared image processing submodule is used to extract target key features from the temperature data features in the infrared thermal image data. The target key features include temperature distribution and hot spot areas. The temperature change trend of the coal pile is analyzed according to the extracted target key features to determine whether there is an abnormal temperature area. The video monitoring processing submodule is used to process the video stream data and perform image recognition on the processed video stream data to determine whether there is any abnormality; The fire prevention warning submodule is used to make comprehensive judgments and warnings based on the judgment results of the infrared image processing submodule and the video monitoring processing submodule, trigger the warning mechanism, and at the same time, send alarm information to relevant personnel.

6. The coal yard environment intelligent monitoring system based on 5G technology as claimed in claim 5 is characterized by: Intelligent monitoring terminal, including: The query and statistics module is used to perform real-time query on all environmental monitoring data and statistics and analysis on historical data, and provides the association, query, statistics and analysis functions of environmental monitoring data; The report generation module is used to generate reports containing detailed information and statistical results based on the data provided by the query statistics module, and to generate various reports according to user needs for visual display; The backend management module is used to access the environmental monitoring data obtained by the monitoring front-end unit in real time, and to monitor the network connection status and equipment operation status of each terminal in real time.

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